ArticleBMC infectious diseases2019
A superiority of viral load over CD4 cell count when predicting mortality in HIV patients on therapy.
Article in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- Randomized Controlled Trial of a Remote Coaching mHealth Adherence Intervention in Youth Living with HIV.AIDS and behavior · 2022Trial
- The efficacy and cost-effectiveness of a family-based economic empowerment intervention (Suubi + Adherence) on suppression of HIV viral loads among adolescents living with HIV: results from a Cluster Randomized Controlled Trial in southern Uganda.Journal of the International AIDS Society · 2021Trial
- Determinants of HIV-1 virologic suppression in HIV-associated tuberculosis in Brazil.Memorias do Instituto Oswaldo Cruz · 2026Observational
- Characteristics of Individuals With Advanced HIV Disease and Risk Factors for Mortality in a Contemporary Cohort in South Africa.Journal of acquired immune deficiency syndromes (1999) · 2026Article
- HIV viral suppression outcomes of Tenofovir- and Abacavir-based antiretroviral regimens among children on ART in Zambia.Frontiers in public health · 2026Article
- CD4 cell count and viral load count association and its joint risk factors among adult TB/HIV co-infected patients: a retrospective follow-up study.BMC research notes · 2025Article
- Development and Spatial External Validation of a Predictive Model of Survival Based on Random Survival Forest Analysis for People Living With HIV and AIDS After Highly Active Antiretroviral Therapy in China: Retrospective Cohort Study.Journal of medical Internet research · 2025Article
- A Multistate Continuous Time-Inhomogeneous Markov Model for Assessing the CD4 Count Dynamics of HIV/AIDS Patients Undergoing Antiretroviral Therapy in KwaZulu-Natal, South Africa.International journal of environmental research and public health · 2025Article
- Robustness of viral load over CD4 cell count in measuring the quality of life of people with HIV at second line regimen in Amhara region.Scientific reports · 2025Article
- Electrochemical microfluidic biosensor for the detection of CD4Microsystems & nanoengineering · 2025Article
- Clinical Determinants Associated With Viral Load Count Among Adult TB/HIV Co-Infected Patients: A Linear Mixed-Effects Model Analysis.Advances in virology · 2025Article
- A likelihood approach to incorporating self-report data in HIV recency classification.Biometrics · 2024Article
- Long-term non-progression and risk factors for disease progression among children living with HIV in Botswana and Uganda: A retrospective cohort study.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2024Article
- Virological Non-Suppression, Non-Adherence and the Associated Factors Among People Living with HIV on Dolutegravir-Based Regimens: A Retrospective Cohort Study.HIV/AIDS (Auckland, N.Z.) · 2024Article
- Impact of Isoniazid Preventive Therapy on Tuberculosis Incidence and Predictors of Tuberculosis Among People Living With HIV/AIDS at Debre Tabor General Hospital, Northwest Ethiopia.Tuberculosis research and treatment · 2024Article
- Human immunodeficiency virus patients with low CD4 counts are more likely to have precancerous polyps identified during index colonoscopy.World journal of gastrointestinal endoscopy · 2023Article
- Strategies of Managing Repeated Measures: Using Synthetic Random Forest to Predict HIV Viral Suppression Status Among Hospitalized Persons with HIV.AIDS and behavior · 2023Article
- Virological Non-Suppression among Newly Diagnosed HIV-Positive Individuals on Dolutegravir-Based Antiretroviral Treatment in Eastern Ethiopia: Follow-Up Study.Tropical medicine and infectious disease · 2023Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundCD4 cell count has been identified to be an essential component in monitoring HIV treatment outcome. However, CD4 cell count monitoring sometimes fails to predict virological failure resulting in unnecessary switch of treatment lines which causes drug resistance and limitations of treatment options. This study assesses the use of both viral load (HIV RNA) and CD4 cell count in the monitoring of HIV/AIDS progression.
methodsTime-homogeneous Markov models were fitted, one on CD4 cell count monitoring and the other on HIV RNA monitoring. Effects of covariates; gender, age, CD4 baseline, HIV RNA baseline and adherence to treatment were assessed for each of the fitted models. Assessment of the fitted models was done using prevalence plots and the likelihood ratio tests. The analysis was done using the "msm" package in R.
resultsResults from the analysis show that viral load monitoring predicts deaths of HIV/AIDS patients better than CD4 cell count monitoring. Assessment of the fitted models shows that viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count.
conclusionFrom this study one can conclude that although patients take more time to achieve a normal CD4 cell count and less time to achieve an undetectable viral load, once the CD4 cell count is normal, mortality risks are reduced. Therefore, both viral load monitoring and CD4 count monitoring can be used to provide useful information which can be used to improve life expectance of patients living with HIV. However, viral load monitoring is a better predictor of HIV/AIDS progression than CD4 cell count and hence viral load is deemed superior.
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